using unmanned aircraft system uas photogrammetry to
play

Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank - PowerPoint PPT Presentation

Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank Erosion along River Corridors 08-Jan-2018 Scott D. Hamshaw, Ph.D., P.E. Project Goals Evaluate UAS-based photogrammetry system Accuracy comparison to SenseFly eBee UAS


  1. Using Unmanned Aircraft System (UAS) Photogrammetry to Monitor Bank Erosion along River Corridors 08-Jan-2018 Scott D. Hamshaw, Ph.D., P.E.

  2. Project Goals ¨ Evaluate UAS-based photogrammetry system ¨ Accuracy comparison to SenseFly eBee UAS ground survey ¨ Geomorphic change measurement Ground survey: RIEGL VZ-1000 TLS TopCon HiperLite+ GPS

  3. What we get from UAS Orthomosaic imagery 1. Computer vision: Structure-from-motion (SfM) & multi-view stereo Photogrammetric point cloud (RGB colorized) 2. Filtering and/or Machine learning Derived products: classification and processing 3. n Digital surface model (DSM) n Digital elevation model (DEM)

  4. Orthomosaic imagery 3.2 cm UAS 0.5 m Ortho 1 m NAIP

  5. Photogrammetric point cloud

  6. Digital elevation and surface models Airborne LiDAR DSM DEM DEM

  7. Accuracy Assessment – X-Sections ¨ 11 cm vertical / 28 cm horizontal

  8. Accuracy Assessment - GCPs

  9. Field Data Collection

  10. Data collection metrics ¨ 43% of survey days rescheduled/shortened ¨ 2-3 person survey team ¨ Direct georeferenecing with sparse GCPs for check Total Length of Mean Length Total days** Number of days Number Year River Surveyed of River per in field for impacted* by of flights (km) Flight (m) surveying weather 2015 55 21.7 395 12 3 2016 18 13.7 760 5 5 2017 17 14.3 843 4 1

  11. Geomorphic Change Detection Volumetric Change Analysis ¨ Difference of DEMs (DoD) ‘12 ALS to ‘17 UAS ¨ Net change of -19,920 m 3

  12. Geomorphic Change Detection Cross Section Analysis 3.5 m 2

  13. UAS for monitoring river corridors ¨ Optimal survey time: early spring ¨ Sparse network of GCPs = check / bias adjustment ¨ Vegetation density dependent ¨ Technology rapidly developing (during project)

  14. Contact Info & Acknowledgements 14 ¨ Scott Hamshaw, Ph.D., P.E. Special thanks to ¤ Vermont EPSCoR | 23 Mansfield Ave, Burlington, VT co-authors: ¤ scott.hamshaw@uvm.edu • Mandar Dewoolkar ¤ 802.324.6221 • Jarlath O’Neil-Dunne • Donna Rizzo Support provided by: ¨ ¤ Vermont Water Resources and Lake Studies Center • Tayler Engel Vermont EPSCoR with (NSF) Grant EPS-1101317 and EPS-1556770 • Jeff Frolik ¤ NSF Graduate Research Fellowship ( Grant No. DGE-0925179NSF) ¤ Robert & Patricia Switzer Foundation ¤ University of Vermont ¤

  15. Supplementary Information Quantifying Streambank Movement and Topography Using Unmanned Aircraft System Photogrammetry with Comparison to Terrestrial Laser Scanning River Research and Applications 33 (8):1354–67. https://doi.org/10.1002/rra.3183.

  16. River corridor vegetation Spring ‘12 Fall ‘15 Spring ‘17 Summer ‘16 Bristol Flats, New Haven River

  17. DoDs – New Haven River 2017 - 2016 2016 - 2012

  18. DoDs – New Haven River 2015 - 2012 2015 - 2012

  19. SB

Recommend


More recommend